Comparison of the Accuracy Between Naive Bayes Classifier and Support Vector Machine Algorithms for Sentiment Analysis in Mobile JKN Application Reviews by Erni Septiani, Tubagus M. Akhriza, Mochamad Husni

“…We use data scraping and labeling processes before performing sentiment analysis. The sentiment analysis process includes text preprocessing and processing (modeling) by dividing the data into 30%, 40%, and 50% test data, with the rest becoming training data. …”
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The phytoplasma SAP54 effector acts as a molecular matchmaker for leafhopper vectors by targeting plant MADS-box factor SVP by Zigmunds Orlovskis, Archana Singh, Adi Kliot, Weijie Huang, Saskia A Hogenhout

“…This study explores the role of the virulence protein SAP54, produced by parasitic phytoplasmas, in attracting leafhopper vectors. SAP54 is responsible for the induction of leaf-like flowers in phytoplasma-infected plants. …”
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Penyeimbangan Kelas SMOTE dan Seleksi Fitur Ensemble Filter pada Support Vector Machine untuk Klasifikasi Penyakit Liver by Muhammad Amir Nugraha, Muhammad Itqan Mazdadi, Andi Farmadi, Muliadi, Triando Hamonangan Saragih

“…Berdasarkan penelitian sebelumnya, metode Support Vector Machine (SVM) paling baik dalam mengklasifikasikan pasien penyakit liver. …”
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SENTIMENT ANALYSIS OF REVIEWS ON X APPS ON GOOGLE PLAY STORE USING SUPPORT VECTOR MACHINE AND N-GRAM FEATURE SELECTION by Fahri Aimar Kusumo, Dewi Retno Sari Saputro, Purnami Widyaningsih

“…Sentiment analysis requires classification algorithms, such as Support Vector Machine (SVM). SVM is a frequently used algorithm for text data classification because it can handle high-dimensional data. …”
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Evaluation of a digital entomological surveillance planning tool for malaria vector control: Three country mixed methods pilot study. by Charlotte Hemingway, Steven Gowelo, Mercy Opiyo, Dulcisaria Marrenjo, Mara Maquina, Blessings N Kaunda-Khangamwa, Lusungu Kayira, Teklu Cherkose, Yohannes Hailemichael, Neusa Torres, Estevao Mucavele, Muanacha Mintade, Baltazar Candrinho, Themba Mzilahowa, Endalamaw Gadisa, Allison Tatarsky, Élodie A Vajda, Emily Dantzer, Edward Thomsen, Michael Coleman, Neil F Lobo

“…<h4>Background</h4>Vector control remains the principal method to prevent malaria transmission and has led to significant reductions in malaria incidence across endemic regions. …”
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Comparison of K-Nearest Neighbor, Support Vector Machine, Random Forest, and C 4.5 Algorithms on Indoor Positioning System by M Rizky Astari, Muhammad Taufiq Nuruzzaman, Bambang Sugiantoro

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Fiber-Optic Vector Magnetic Field Sensor Based on Mode Interference and Magnetic Fluid in a Two-Channel Tapered Structure by He Tian, Yuxiao Song, Yanzeng Li, Hanyang Li

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Sentiment Analysis of User Reviews of the KitaLulus Application on Google Play Store using the Support Vector Machine (SVM) Algorithm by Ahmad Syaifudin Agil Rafsanjani, Diana Laily Fithri, Supriyono Supriyono

“…This study aims to analyze user sentiment toward the KitaLulus application using the Support Vector Machine (SVM) algorithm, combined with the Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance in sentiment data. …”
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Implementation of the Support Vector Machine (SVM) Algorithm on Sentiment Analysis of Public Opinion on The Prohibition of the use of Syrupy Drugs for Kidney Health by Galih Purnomo, Rumini Rumini, Tri Susanto

“…This research concludes that the Support Vector Machine (SVM) algorithm with a linear kernel achieves the highest accuracy in sentiment analysis.…”
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Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines by E León, A Li, M A Bahena Schott, B Bos, M Busch, J R Chapman, G L Duran, J Gruszko, R Henning, E L Martin, J F Wilkerson

“…We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. …”
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High resistance fault detection in DC microgrid using Hilbert Huang transform and vector-based ensemble optimized LSTM networks by H. K. Prashanth Kumar, Ritesh Dash, K. Jyotheeswara Reddy, Nageswara Rao Atyam, Bhabasis Mohapatra

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Implementasi Chatbot pada Telegram sebagai Monitoring Assistant dengan Analisis Teks Klasifikasi Menggunakan Metode Support Vector Machine by Dwi Lestari, Lukman Subekti

“…Tujuan dari penelitian ini adalah membuat klasifikasi intent pada chatbot dengan menggunakan teknologi Natural Language Processing dan algoritma Support Vector Machine (SVM). …”
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Feature Extraction and Classification of Power Quality Disturbances Using Optimized Tunable-Q Wavelet Transform and Incremental Support Vector Machine by Indu Sekhar Samanta, Pravat Kumar Rout, Kunjabihari Swain, Satyasis Mishra, Murthy Cherukuri

“…The proposed hybrid approach is comprised of an optimized tunable-Q wavelet transform (OTQWT) for the feature extraction and incremental support vector machine (ISVM). A four-stage approach is suggested for the PQ detection and classification in this study. …”
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Rapid Identification of Nine Easily Confused Mineral Traditional Chinese Medicines Using Raman Spectroscopy Based on Support Vector Machine by Jing Ming, Long Chen, Yan Cao, Chi Yu, Bi-Sheng Huang, Ke-Li Chen

“…Mineral traditional Chinese medicines (TCMs) are natural minerals, mineral processing products, and some fossils of animals or animal bones that can be used as medicines. …”
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A Dual-Stream Deep Learning Architecture With Adaptive Random Vector Functional Link for Multi-Center Ischemic Stroke Classification by Mahesh Anil Inamdar, Anjan Gudigar, U. Raghavendra, Massimo Salvi, Raja Rizal Azman Bin Raja Aman, Nadia Fareeda Muhammad Gowdh, Izzah Amirah Binti Mohd Ahir, Mohd Salahuddin Bin Kamaruddin, Khairul Azmi Abdul Kadir, Filippo Molinari, Ajay Hegde, Girish R. Menon, U. Rajendra Acharya

“…Three significant innovations are included in the suggested architecture: (1) a hybrid Dual Attention Mechanism that combines Dynamic Routing and Cross-Attention for improved region-specific feature discrimination; (2) a Multi-Scale Feature Extraction Module with parallel convolutional pathways that captures both contextual and fine-grained features; and (3) an Adaptive Random Vector Functional Link layer that significantly reduces training time while maintaining high classification performance. …”
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Implementation of Insecticide for Fogging and Larvicidation in Dengue Fever Control and Its Impact on Vector Resistance in Banjarmasin City: A Qualitative Analysis by Juhairiyah, Muhammad Rasyid Ridha, Liestiana Indriyati, Ririh Yudhastuti, Triwibowo Ambar Garjito, Muhammad Choirul Hidajat, Wahyu Pudji Nugraheni, Nurul Hidayah, Isnawati, Babucarr Jassey

“…Insecticide-based interventions, such as fogging and larviciding, are key components of dengue vector control. However, improper implementation can lead to insecticide resistance, reducing program effectiveness. …”
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On the basis of the hypothesis of local determinacy in the theory of elasto- plastic processes by Dao Huy Bich, Duong Tat Thang

“… The hypothesis of local determinancy gives concrete relations of elasto - Plastic processes, where functional of the qrientation and the capacity of stresses vector can be represented as a solution of the set of non - linear ordinary differential equations the behaviours of these functional are studied in the general case on this basis the boundary valuable problem in the theory of plasticity is exactly formulated. …”
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Prediction Model For Students' On-Time Graduation Using Algorithm Support Vector Machine (SVM) Based  Particle Swarm Optimization (PSO) by Syarif Hidayatulloh, Gandung Triyono, Kiki Ari Suwandi kosasih

“…This research aims to create a prediction model for graduating on time using the Support Vector Machine (SVM) method based on Particle Swarm Optimization (PSO) with feature selection. information gain, so that the attributes selected and used are Semester Achievement Index 1, Semester Achievement Index 2, Semester Achievement Index 3, Semester Achievement Index 4, Grade Point Average (GPA) 1, Grade Point Average (GPA) 2, Grade Point Average (GPA) 3, Grade Point Average (GPA) 4, Semester Credit Units 1, and Semester Credit Units 4. …”
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Leishmania major glycosylation mutants require phosphoglycans (lpg2-) but not lipophosphoglycan (lpg1-) for survival in permissive sand fly vectors. by Anna Svárovská, Thomas H Ant, Veronika Seblová, Lucie Jecná, Stephen M Beverley, Petr Volf

“…The sand fly species used were the permissive species Phlebotomus perniciosus and P. argentipes, and the specific vector P. duboscqi, a species resistant to L. infantum development.…”
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PREDICTION MODEL FOR STUDENTS' ON-TIME GRADUATION USING ALGORITHM SUPPORT VECTOR MACHINE (SVM) BASED  PARTICLE SWARM OPTIMIZATION (PSO) by Syarif Hidayatulloh, Gandung Triyono, Kiki Ari Suwandi kosasih

“…This research aims to create a prediction model for graduating on time using the Support Vector Machine (SVM) method based on Particle Swarm Optimization (PSO) with feature selection. information gain, so that the attributes selected and used are Semester Achievement Index 1, Semester Achievement Index 2, Semester Achievement Index 3, Semester Achievement Index 4, Grade Point Average (GPA) 1, Grade Point Average (GPA) 2, Grade Point Average (GPA) 3, Grade Point Average (GPA) 4, Semester Credit Units 1, and Semester Credit Units 4. …”
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